{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "实验1+：pandas\n",
    "1. iris数据集，画出sepal_length字段，将直方图和密度图画在一张图里。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "url = 'https://www.gairuo.com/file/data/dataset/iris.data'\n",
    "df = pd.read_csv(url)\n",
    "\n",
    "ax = df['sepal_length'].plot.hist(density=True)\n",
    "df['sepal_length'].plot.kde(ax = ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "2. 数据2 中北京、上海、江苏、广东四个省的数据，画出线图、柱状图、饼图\n",
    "其中线图画所有年份趋势， 柱状图画2016年四省对比，饼图画所有年汇总。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x118b8710ca0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "gdf = pd.read_csv(\"C:/Users/猪猪的电脑/Desktop/需要提交的作业/gdp.csv\").set_index('province')\n",
    "four = gdf.iloc[[0,8,9,18]]\n",
    "four.T.sort_index().plot.line()\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "\n",
    "four['2016y'].plot.bar(rot = 0)\n",
    "\n",
    "four.T.sum().plot.pie()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3. 数据1中，去掉第一行全国数据。通过散点图找出和forcible_rape最相关和最不相关的两列（相关就是y轴随X轴变化），\n",
    "以两个子图形式画出，且每个点大小用population除以300000来控制。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "df = pd.read_csv(\"C:/Users/猪猪的电脑/Desktop/需要提交的作业/crime.csv\").loc[1:]\n",
    "fig, axes = plt.subplots(1,2)\n",
    "\n",
    "df.plot.scatter(x = 'forcible_rape', y = 'murder', s = df['population']//300000,ax = axes[0])\n",
    "#df可改\n",
    "df.plot.scatter(x = 'forcible_rape', y = 'burglary', s = df['population']//300000 ,ax = axes[1])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
